A neurocomputational theory of action regulation predicts motor behavior in neurotypical individuals and patients with Parkinson's disease.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
11 2022
Historique:
received: 20 04 2022
accepted: 27 10 2022
revised: 01 12 2022
pubmed: 18 11 2022
medline: 6 12 2022
entrez: 17 11 2022
Statut: epublish

Résumé

Surviving in an uncertain environment requires not only the ability to select the best action, but also the flexibility to withhold inappropriate actions when the environmental conditions change. Although selecting and withholding actions have been extensively studied in both human and animals, there is still lack of consensus on the mechanism underlying these action regulation functions, and more importantly, how they inter-relate. A critical gap impeding progress is the lack of a computational theory that will integrate the mechanisms of action regulation into a unified framework. The current study aims to advance our understanding by developing a neurodynamical computational theory that models the mechanism of action regulation that involves suppressing responses, and predicts how disruption of this mechanism can lead to motor deficits in Parkinson's disease (PD) patients. We tested the model predictions in neurotypical individuals and PD patients in three behavioral tasks that involve free action selection between two opposed directions, action selection in the presence of conflicting information and abandoning an ongoing action when a stop signal is presented. Our results and theory suggest an integrated mechanism of action regulation that affects both action initiation and inhibition. When this mechanism is disrupted, motor behavior is affected, leading to longer reaction times and higher error rates in action inhibition.

Identifiants

pubmed: 36395336
doi: 10.1371/journal.pcbi.1010111
pii: PCOMPBIOL-D-22-00614
pmc: PMC9714880
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1010111

Subventions

Organisme : NINDS NIH HHS
ID : U01 NS098961
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS097782
Pays : United States

Informations de copyright

Copyright: © 2022 Zhong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Shan Zhong (S)

Neuroscience graduate program, University of California Riverside, Riverside, California, United States of America.

Jeong Woo Choi (JW)

Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, Texas, United States of America.

Nadia G Hashoush (NG)

David Geffen Sch. of Med., University of California Los Angeles, Los Angeles, California, United States of America.

Diana Babayan (D)

David Geffen Sch. of Med., University of California Los Angeles, Los Angeles, California, United States of America.

Mahsa Malekmohammadi (M)

David Geffen Sch. of Med., University of California Los Angeles, Los Angeles, California, United States of America.

Nader Pouratian (N)

Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, Texas, United States of America.

Vassilios Christopoulos (V)

Neuroscience graduate program, University of California Riverside, Riverside, California, United States of America.
Department of Bioengineering, University of California Riverside, Riverside, California, United States of America.

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